Predicting the impact of environmental factors on citrus canker through multiple regression

Climatic conditions play a significant role in the development of citrus canker caused by Xanthomonas citri pv . citri ( Xcc ). Citrus canker is regarded as one of the major threats being faced by citrus industry in citrus growing countries of the world. Climatic factors exert significant impacts on growth stage, host susceptibility, succulence, vigor, survival, multiplication rate, pathogen dispersion, spore penetration rate, and spore germination. Predicting the impacts of climatic factors on these traits could aid in the development of effective management strategies against the disease. This study predicted the impacts of environmental variables, i.e., temperature, relative humidity, rainfall, and wind speed the development of citrus canker through multiple regression. These environmental variables were correlated with the development of canker on thirty (30) citrus varieties during 2017 to 2020. Significant positive correlations were noted among environment variables and disease development modeled through multiple regression model (Y = +24.02 + 0.5585 X1 + 0.2997 X2 + 0.3534 X3 + 3.590 X4 + 1.639 X5). Goodness of fit of the model was signified by coefficient determination value (97.5%). Results revealed the optimum values of environmental variables, i.e., maximum temperature (37˚C), minimum temperature (27˚C), relative humidity (55%), rainfall (4.7–7.1 mm) and wind speed (8 Km/h), which were conducive for the development of citrus canker. Current study would help researchers in designing better management strategies against citrus canker disease under changing climatic conditions in the future.


Data collection
This three-year study collected citrus canker disease incidence data from the experimental area of Department of Plant Pathology, University of Agriculture Faisalabad, Pakistan. Data relating to environmental variables including maximum and minimum temperatures (˚C), wind speed (Km/h), rainfall (mm) and relative humidity (%) were obtained from meteorological station located at Agronomy research area, University of Agriculture Faisalabad, Pakistan. The relationship of these environmental variables with the disease development was predicted by regression and correlation analysis and a predictive model was developed based on the obtained results.

Regression analysis
Regression analysis was used to determine the relationship between environmental variables and disease development/incidence [36,37]. Two different regression models, i.e., simple, and multiple regression models were used in the study. The mathematical equations for these models are presented as Eq 1 and Eq 2.
Here, Y acts as response variable in case of disease, while X works as explanatory variable. The β0 denotes as intercept and β1 is the slope.
For multiple linear regression models, more than one explanatory or predictor variables (X) are included as compared to the simple linear regression analysis.
Here, x characterizes the compilation of predictors x1, x2,. . . xi in the model, and β1, β2,. . . βi act for the corresponding regression coefficients and 2 is the random error or interruption in the experiment [38,39].

Characterization of environmental factors conducive for citrus canker
All environmental data as well as disease incidence (%), and alterations in the environmental factors and disease incidence were analyzed by least significant difference test (LSD at P<0.05) [40]. The effect of environmental factors on citrus canker disease was modeled by correlation. Mean square error (MSE) Mallows Cp and R 2 were used a criteria for selecting the best models [41,42].

Goodness of fit of the model
The correlation was used for determining the goodness of fit of the model [43][44][45]. The varieties/cultivars in which >50% of the environmental variables exerted significant effect were plotted and most conducive environmental factors for disease development were determined. The manipulation of these factors on disease infestation was tested by drawing a comparison between observed and predicted disease incidence values by multiple regression models [45,46]. Furthermore, disease predictive model depending on environmental conditions was developed which has significant influence on citrus canker disease development.

Statistical analysis
The data consisted of an average of three replicates and differences among treatments were estimated by one-way analysis of variance (ANOVA). The means were compared using least significant difference post-hoc test (P < 0.05) where ANOVA indicated significant differences. All statistical computations were made on SPSS 20.0 [47]. Microsoft excel 2016 was used to calculate the standard errors of the meas. Graphical presentation was completed on Origin Pro 9.0 (OriginPro, Northampton, USA). The minimal dataset of the study has been uploaded as S1 Dataset.

Development and evaluation of citrus canker predictive model
Multiple regression equation of citrus canker predictive model for two years was Y = +24.02 + 0.5585 X 1 + 0.2997 X 2 + 0.3534 X 3 + 3.590 X 4 + 1.639 X 5 . Here (Y = disease incidence X 1 = maximum temperature, X 2 = minimum temperature, X 3 = relative humidity, X 4 = rainfall and X 5 = wind speed). The R 2 value expressed that model was statistically fitted well for environmental variables. Some data points deviated from the reference line according to the normal probability (Fig 1), while most values were scattered equally around the residual line in case of residual vs. fit model which showed better fit (Fig 2). Few data points were little far from the line of reference i.e., near to zero; -3.5 to + 4 primarily exhibited as an error in the regression model. Model was designed according to [36].

Assessment of disease predictive model by comparing dependent variables with regression coefficient through physical theory
Analysis of variance of regression articulated that maximum and minimum temperature, relative humidity, rainfall, and wind speed significantly contributed towards disease development. The R 2 value of 97.5% expressed that model was statistically suitable under given environmental conditions. Variable's coefficients of regression model for citrus canker are given in Table 1.

Estimation of model for predicted and observed values
For assessing the reliability of model, value differences of observed and predicted data points were estimated. Among observed values, fourteen data points were beyond reference line (standard error = 1.81517) and created an error in experiment. According to graphs, maximum prediction (464 out of 480 values) values have differences (less than 5) were consolidated between 95% confidence interval (C.I) and 95% predictive interval (P.I) which showed that there was a good fit between predictive and observed values (Fig 3).

Correlation of environmental variables with the development of citrus canker disease on various citrus varieties during 2017-18 and 2018-19
Maximum and minimum temperature, relative humidity, rainfall and wind speed had significant positive correlation (P� 0.05) with citrus canker incidence during both years on thirty varieties (

Characterization of environmental factors conducive for the development of citrus canker disease on five varieties during 2017-18 and 2018-19
Five citrus varieties, i.e., Jaffa, Kagzi lime, Mayer lemon, Succari and Grapefruit were used for the determination of environmental factors conducive for the development of citrus canker. All environmental variables had positive significant correlation with citrus canker on all varieties during both years. The highest disease incidence (up to 55%) was recorded for Grapefruit under 37.2˚C maximum temperature, while low disease incidence (7%) was observed on Jaffa under 37˚C (Fig 4). Minimum disease incidence of 7% and less than 8% was noticed on Jaffa under 27.9˚C minimum temperature ( Fig 5). Jaffa showed 6.5% disease incidence during both years under 79.8% relative humidity as compared to disease incidence on Kagzi lime (18.9%), Mayer lemon (25.8%), Succari (40.5%) and Grapefruit (55.7%) (Fig 6). The similar variety Grapefruit showed 55.7% disease incidence 7.3 mm and 4.9 mm rainfall during 1 st and 2 nd year, respectively. Jaffa expressed relatively low disease incidence (<7%) (Fig 7). Disease incidence of less than 10% was recorded on Jaffa under 8 km/h wind speed during 2017 and 2018 (Fig 8). It was noticed that disease incidence increased from 8.5 to 55.7 and 8 to 55.4% on Grapefruit with rain splashes increasing, during both 2017-18 and 2018-19, respectively and same pattern was observed on all other varieties.

Discussion
Host susceptibility, pathogen virulence and favorable environmental conditions are necessary for disease development. Environmental factors like temperature, rainfall, wind speed, and relative humidity are crucial elements for different diseases [48,49]. Sudden fluctuations in these All environmental factors expressed significant positive correlation with all tested varieties/ cultivars in the present study. The highest disease incidence was observed under 20-28˚C and 30-38˚C minimum and maximum temperature, 47-74% relative humidity, 8 km/h wind speed and 4 mm rainfall during both years. Predictive model based upon two years data was developed, Y = +24.02 + 0.5585 X 1 + 0.2997 X 2 + 0.3534 X 3 + 3.590 X 4 + 1.639 X 5 (Y = disease incidence X 1 = maximum temperature, X 2 = minimum temperature, X 3 = relative humidity, X 4 = rainfall and X 5 = wind speed). The R 2 value of 97.5% expressed that that model is  [59,60]. Different plant diseases and pathogens prefer different lower and higher temperatures. Some bacterial pathogens like Pseudomonas grow

PLOS ONE
Predicting the impact of environmental factors on citrus canker through multiple regression faster in the presence of low temperature, while others like Xanthomonas and Ralstonia grow much faster under high temperature. Temperature is also responsible in favoring and inhibiting the expression of certain genes, rapid production of pathogenesis related proteins involved in disease resistance and susceptibility by affecting the genetic machinery of host cells [61,62].
In contemporary studies, temperature (maximum and minimum) relative humidity, strong wind with heavy rainfall gave significant correlation with citrus canker disease on maximum varieties. A strong interaction between disease development and increase in relative humidity was seen, which has been witnessed in earlier studies [63,64]. Pathogen can spread up-to 50 km/h in the high wind speed and by reducing wind speed in orchards can reduced the dispersal of Xcc [65,66]. Rainfall also expressed highly positive correlation with the development of disease. Incidence of canker disease was significantly increased with increasing in rainfall [35]. These results were supported by some recent studies [21,67] reporting that temperature with other environmental factors had a major role in disease development. Disease index of citrus canker was highest under increased temperature and relative humidity during the month of July followed by month of August and September [68,69]. High precipitation with sharp wind also contributed in the multiplication of bacteria. The incidence of citrus canker was greater when the rainy season started in the month of September [70,71]. The winds also take part in the prevalence of diseases by spreading the pathogens, increasing the number of lesions and somehow by accelerating the drying of wet surfaces of the plants. It also facilitates bacteria in releasing spores and transferred form diseased portions to healthy ones. Results of the present study are also supported by an early study [72] indicating that wind becomes more drastic and lethal when it is accompanied by heavy rain, especially for citrus canker. These wind-blown rain splashes caused injuries on the surface of plants which help a number of bacteria and other pathogens to get entry into the plants [42]. Rainstorm during monsoon also increases the epidemics of various bacterial diseases in the presence of active source of inoculum and spread through strong winds [73].

Conclusion
All the environmental variables, i.e., maximum, and minimum temperature, relative humidity, rainfall, and wind speed had significant positive correlation with citrus canker development on all varieties. Due to sudden fluctuations in the weather conditions, continuous monitoring of environmental variables is necessary for accurate prediction of citrus canker and its management. Installation of weather stations in major citrus growing areas would be helpful in risk assessment and forecasting systems in a specific area. Based on data collected from different areas, a Decian Support System can be developed for precise management of disease.